4.7 Article

NetSquid, a NETwork Simulator for QUantum Information using Discrete events

期刊

COMMUNICATIONS PHYSICS
卷 4, 期 1, 页码 -

出版社

NATURE RESEARCH
DOI: 10.1038/s42005-021-00647-8

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资金

  1. Dutch Research Cooperation Funds (SMO)
  2. European Research Council
  3. QIA project - (European Union's Horizon 2020) [820445]
  4. Netherlands Organisation for Scientific Research (NWO/OCW), as part of the Quantum Software Consortium programme [024.003.037/3368]

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NetSquid is a discrete-event based platform for simulating quantum networks and modular quantum computing systems, showcasing its power in studying various use cases such as detailed physical layer simulations and control plane analysis. The platform demonstrates the ability to investigate large networks and implement large-scale quantum communication systems.
In order to bring quantum networks into the real world, we would like to determine the requirements of quantum network protocols including the underlying quantum hardware. Because detailed architecture proposals are generally too complex for mathematical analysis, it is natural to employ numerical simulation. Here we introduce NetSquid, the NETwork Simulator for QUantum Information using Discrete events, a discrete-event based platform for simulating all aspects of quantum networks and modular quantum computing systems, ranging from the physical layer and its control plane up to the application level. We study several use cases to showcase NetSquid's power, including detailed physical layer simulations of repeater chains based on nitrogen vacancy centres in diamond as well as atomic ensembles. We also study the control plane of a quantum switch beyond its analytically known regime, and showcase NetSquid's ability to investigate large networks by simulating entanglement distribution over a chain of up to one thousand nodes. Implementing large-scale quantum networks is one of the challenges at the core of quantum communication. Here, the authors present NetSquid, a quantum network simulator that allows studying how such networks can be built, including physical hardware modelling, modularity, scalability, and examples.

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